def doday():
"""
Create a plot of precipitation stage4 estimates for some day
"""
sts = mx.DateTime.DateTime(2013,5,25,12)
ets = mx.DateTime.DateTime(2013,5,31,12)
interval = mx.DateTime.RelativeDateTime(days=1)
now = sts
total = None
while now < ets:
fp = "/mesonet/ARCHIVE/data/%s/stage4/ST4.%s.24h.grib" % (
now.strftime("%Y/%m/%d"),
now.strftime("%Y%m%d%H") )
if os.path.isfile(fp):
lts = now
grbs = pygrib.open(fp)
if total is None:
g = grbs[1]
total = g["values"]
lats, lons = g.latlons()
else:
total += grbs[1]["values"]
grbs.close()
now += interval
m = MapPlot(sector='iowa', title='NOAA Stage IV & Iowa ASOS Precipitation',
subtitle='25-30 May 2013')
m.pcolormesh(lons, lats, total / 25.4, numpy.arange(0,14.1,1), latlon=True,
units='inch')
m.drawcounties()
m.plot_values(dlons, dlats, dvals, '%.02f')
m.postprocess(filename='test.svg')
import iemplot
iemplot.makefeature('test')
row = ccursor.fetchone()
days.append( row[1] )
import matplotlib.pyplot as plt
import numpy
days = numpy.array( days )
fig = plt.figure()
ax = fig.add_subplot(111)
rects = ax.bar( numpy.arange(1880,2013) - 0.4, days, facecolor='b', edgecolor='b')
for rect in rects:
if rect.get_height() >= days[-1]:
rect.set_edgecolor('r')
rect.set_facecolor('r')
ax.set_xlim(1879.5, 2012.5)
ax.set_ylim(20, 70)
ax.set_ylabel("Average High Temperature $^{\circ}\mathrm{F}$")
ax.set_title("Des Moines [1880-2012] Average High Temperature \n for week before Thanksgiving (inclusive)")
ax.set_xlabel("* 2012 Warmest")
#ax.set_xticks( numpy.arange(1895,2015,5) )
ax.grid(True)
import iemplot
fig.savefig('test.ps')
iemplot.makefeature('test')
#for i in range(7):
# print i, total_error[i] / 117.0, total_rain[i] / 117.0, total_snow[i] / 117.0
ax[row, col].set_xticklabels(
('May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'))
ax[row, col].set_xlim(120, 310)
ax[row, col].grid(True)
ax[row, col].set_ylim(0, 100)
if col == 0:
ax[row, col].set_ylabel("Coverage [%]")
ax[row, col].set_title(" ")
ax[row, col].text(126, 85, states[i].capitalize(), size=16)
i += 1
#ax[0,0].set_title("USDA Weekly Crop Progress Report (1979-2012)\nIowa Corn Planting Progress (6 years highlighted)")
fig.text(
0.5,
.91,
'USDA Weekly Corn Crop Condition Report (1986-2014)\nPercentage of State in Poor & Very Poor Condition\n(2014 thru 24 August)',
ha='center')
logo = Image.open('../../../htdocs/images/logo_small_white.png')
ax3 = plt.axes([0.12, 0.91, 0.1, 0.1],
frameon=False,
axisbg=(0.4471, 0.6235, 0.8117),
yticks=[],
xticks=[])
ax3.imshow(logo)
fig.savefig('test.ps')
import iemplot
iemplot.makefeature('test')
vals = []
lats = []
lons = []
icursor.execute("""SELECT id, x(geom) as lon, y(geom) as lat,
min(min_tmpf) from summary_2012 s JOIN stations t on (t.iemid = s.iemid)
WHERE network IN ('IA_ASOS','AWOS')
and min_tmpf < 60 and day >= '2012-04-08' and id not in ('CIN', 'TNU')
GROUP by id, lon, lat ORDER by min DESC""")
for row in icursor:
vals.append( row[3] )
lats.append( row[2] )
lons.append( row[1] )
print row
cfg = {
'wkColorMap': 'BlAqGrYeOrRe',
'nglSpreadColorStart': 2,
'nglSpreadColorEnd' : -1,
'_title' : "2012 April Minimum Temperature",
'_valid' : "April 8th thru 11th",
'_showvalues' : True,
'_format' : '%.0f',
'lbTitleString' : "[F]",
}
# Generates tmp.ps
fp = iemplot.simple_contour(lons, lats, vals, cfg)
#iemplot.postprocess(fp, '','')
import iemplot
iemplot.makefeature(fp)
"NECLIMATE", "KSCLIMATE", "MOCLIMATE", "KYCLIMATE", "ILCLIMATE", "WICLIMATE",
"INCLIMATE", "OHCLIMATE", "MICLIMATE"))
ccursor.execute("""
select march.station, march.avg - april.avg as diff from (select station, avg((high+low)/2.0) from alldata WHERE year = 2012 and month = 3 GROUP by station) as march, (select station, avg((high+low)/2.0) from alldata WHERE year = 2012 and month = 4 GROUP by station) as april WHERE march.station = april.station ORDER by diff DESC
""")
vals = []
lats = []
lons = []
for row in ccursor:
station = row[0]
if not nt.sts.has_key(station):
continue
vals.append( row[1] )
lats.append( nt.sts[station]['lat'] )
lons.append( nt.sts[station]['lon'] )
cfg = {'_title': "2012 March versus April Average Temperature",
'_valid': '(preliminary data) Postive values are warmer March than April',
'lbTitleString': 'F',
#'wkColorMap': 'ViBlGrWhYeOrRe',
'wkColorMap': 'BlWhRe',
'cnLevelSelectionMode': 'ManualLevels',
'cnLevelSpacingF' : 1.0,
'cnMinLevelValF' : -8.0,
'cnMaxLevelValF' : 8.0,
'_midwest': True}
tmpfp = iemplot.simple_contour(lons, lats, vals, cfg)
iemplot.makefeature(tmpfp)
tsigma = np.array(tsigma, "f")
psigma = np.array(psigma, "f")
ax.quiver(
tsigma[:-1],
psigma[:-1],
tsigma[1:] - tsigma[:-1],
psigma[1:] - psigma[:-1],
scale_units="xy",
angles="xy",
scale=1,
zorder=1,
color="tan",
)
for l, t, p, a in zip(lbls, tsigma, psigma, aligns):
# Manual move label some for readiability
if l == "7/15":
t = float(t) + 0.1
p = float(p) + -0.2
ax.text(t, p, l, va=a, zorder=2)
ax.set_xlim(-3.5, 3.5)
ax.set_ylabel("Precipitation Departure $\sigma$")
ax.set_xlabel("Temperature Departure $\sigma$")
ax.set_title("26 May 2014 - 8 Sep 2014 Iowa\n 14 Day Trailing Departures plotted every 7 days")
ax.grid(True)
fig.savefig("test.ps")
import iemplot
iemplot.makefeature("test")